This project examines the extent to which predatory pricing and limit pricing arise in the Markov-perfect equilibrium of a model of industry dynamics in which firms face the prospect of learning-by-doing and organizational forgetting. A variety of standards for predatory pricing are applied, including the traditional Areeda & Turner (1975) standard of pricing below average variable cost and economic tests proposed by a number of scholars (e.g., Ordover & Willig (1981) and Cabral & Riordan (1997)). To date, there has been no work showing how economic and legal definitions of predatory pricing can be operationalized in a dynamic model of price competition with entry and exit, nor has there been a comprehensive analysis of the extent to which predation arises in equilibrium in such a model. In addition, there has been no work on the welfare effects of a ban on predatory pricing in a fully dynamic model. This research attempts to fill these gaps.
Predatory pricing has been a contentious area of antitrust policy, with some scholars (e.g., McGee 1980) suggesting that predatory pricing is rare and ineffective, and other scholars (most notably, Kreps, Milgrom, Roberts, and Wilson in several papers) showing that predatory behavior can arise as an equilibrium phenomenon if firms are concerned with establishing a reputation for toughness. When learning economies are present, distinguishing predatory from non-predatory behavior is especially challenging because firms have both predatory and non-predatory reasons to charge a price below out-of-pocket cost. The non-predatory reason is that below-cost pricing makes it more likely that the firm moves further down its learning curve; even a monopolist may engage in below-cost pricing for this reason. The predatory reason is that by moving down its learning curve faster than its rivals, a firm may induce its rivals to exit the industry and make it unattractive for new entrants to come into the industry. The difficulty distinguishing predatory from non-predatory pricing was an issue in evaluating the pricing behavior of Japanese firms in the market for DRAM chips in the 1980s and 1990s (Flamm 1996).
Broader impacts: This research is expected to have a broader social impact beyond its contributions to the theoretical literature in industrial organization (IO). Over the past few years, the IO literature has made considerable progress in analyzing the dynamics of an industry, and the equilibria of large dynamic stochastic games can now be computed fairly easily (even when there are multiple equilibria). In addition, scholars have made great advances in estimating the primitives of such dynamic models. In light of these advances, this analysis is expected to be an important step forward in providing agencies charged with developing and enforcing antitrust policy with a tool to determine in particular cases whether firms are likely to engage in predatory behavior and what the welfare consequences of a policy intervention are likely to be. More generally, this research is a step toward the goal of making dynamic analysis a standard methodology to answer questions of public policy.
